Institutional Repository of Key Laboratory of Ocean Circulation and Wave Studies, Institute of Oceanology, Chinese Academy of Sciences
Statistical Bias Correction for Simulated Wind Speeds Over CORDEX-East Asia | |
Li, Delei1,2,3; Feng, Jianlong4; Xu, Zhenhua1,2,3; Yin, Baoshu1,2,3,5; Shi, Hongyuan6; Qi, Jifeng1,2,3 | |
2019-02-01 | |
发表期刊 | EARTH AND SPACE SCIENCE |
ISSN | 2333-5084 |
卷号 | 6期号:2页码:200-211 |
通讯作者 | Xu, Zhenhua([email protected]) ; Yin, Baoshu([email protected]) |
摘要 | Surface wind is significant for ocean state climate, ocean mixing, and viability of wind energy techniques. However, surface wind simulated from the regional climate model generally features substantial bias from observation. For the first time, this study compares the performance of five bias correction techniques, (1) linear scaling, (2) variance scaling, (3) quantile mapping based on empirical distribution, (4) quantile mapping based on Weibull distribution, and (5) cumulative distribution functions transformation, in reducing the statistical bias of a regional climate model wind output, which was downscaled from a global climate model CNRM-CM5 during 1991-2000. The surface wind of JRA55 reanalysis data is used as reference. Results show that all bias correction methods are consistent in reducing the climatological mean bias in spatial patterns and intensities. The linear scaling method always performs the worst among all methods in correcting higher-order statistical biases such as skewness, kurtosis, and wind power density. The other four bias correction methods are generally similar in reducing the statistical biases of different measures based on spatial distribution maps. However, when it comes to spatial averaged mean of statistical measures over CORDEX-East Asia in January and July, the quantile mapping based on Weibull distribution generally shows the best skills among all methods in bias reduction. Plain Language Summary In the current stage, global climate model or regional climate model simulations generally feature substantial bias relative to observations, leading to an inaccurate assessment of climate change or inaccurate inputs for impact models. For the first time, we have compared five bias correction methods using various statistical measures to find out the most robust method for correcting statistical properties of simulated winds from regional climate model. Results show that the linear scaling method always performs the worst among all methods in correcting higher-order statistical biases of simulated winds. On average, the quantile mapping based on Weibull distribution shows the best skills among all methods in bias reduction in January and July. This study is of importance for climate change assessment of wind as well as deriving accurate wind forcing for driving ocean model. |
DOI | 10.1029/2018EA000493 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | China Postdoctoral Science Foundation[2017T100520]###335; China Postdoctoral Science Foundation[2017M612357]###334; National Key Research and Development Program of China[2017YFA0604102]###333; National Key Research and Development Program of China[2017YFA0604101]###332; Strategic Pioneering Research Program of CAS[XDA19060202]###331; Strategic Pioneering Research Program of CAS[XDA22050202]###330; National Natural Science Foundation of China[91858103]###329; National Natural Science Foundation of China[41706020]###328; National Natural Science Foundation of China[41706019]###327; National Natural Science Foundation of China[41706019]; National Natural Science Foundation of China[41706020]; National Natural Science Foundation of China[91858103]; Strategic Pioneering Research Program of CAS[XDA22050202]; Strategic Pioneering Research Program of CAS[XDA19060202]; National Key Research and Development Program of China[2017YFA0604101]; National Key Research and Development Program of China[2017YFA0604102]; China Postdoctoral Science Foundation[2017M612357]; China Postdoctoral Science Foundation[2017T100520] |
WOS研究方向 | Astronomy & Astrophysics ; Geology |
WOS类目 | Astronomy & Astrophysics ; Geosciences, Multidisciplinary |
WOS记录号 | WOS:000460720500001 |
出版者 | AMER GEOPHYSICAL UNION |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.qdio.ac.cn/handle/337002/155295 |
专题 | 海洋环流与波动重点实验室 |
通讯作者 | Xu, Zhenhua; Yin, Baoshu |
作者单位 | 1.Chinese Acad Sci, Inst Oceanol, CAS Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China 2.Chinese Acad Sci, Ctr Ocean Megasci, Qingdao, Peoples R China 3.Pilot Natl Lab Marine Sci & Technol Qingdao, Qingdao, Peoples R China 4.Tianjin Univ Sci & Technol, Coll Marine & Environm Sci, Tianjin, Peoples R China 5.Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing, Peoples R China 6.Ludong Univ, Sch Civil Engn, Yantai, Peoples R China |
第一作者单位 | 中国科学院海洋研究所; 中国科学院海洋大科学研究中心 |
通讯作者单位 | 中国科学院海洋研究所; 中国科学院海洋大科学研究中心 |
推荐引用方式 GB/T 7714 | Li, Delei,Feng, Jianlong,Xu, Zhenhua,et al. Statistical Bias Correction for Simulated Wind Speeds Over CORDEX-East Asia[J]. EARTH AND SPACE SCIENCE,2019,6(2):200-211. |
APA | Li, Delei,Feng, Jianlong,Xu, Zhenhua,Yin, Baoshu,Shi, Hongyuan,&Qi, Jifeng.(2019).Statistical Bias Correction for Simulated Wind Speeds Over CORDEX-East Asia.EARTH AND SPACE SCIENCE,6(2),200-211. |
MLA | Li, Delei,et al."Statistical Bias Correction for Simulated Wind Speeds Over CORDEX-East Asia".EARTH AND SPACE SCIENCE 6.2(2019):200-211. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Statistical Bias Cor(18193KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 浏览 |
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